Data Mining in SQL Server 2005

Slides:



Advertisements
Similar presentations
Business Intelligence Microsoft. Improving organizations by providing business insights to all employees leading to better, faster, more relevant decisions.
Advertisements

Annop Siritikul Account Technology Specialist Microsoft (Thailand) “Transform Data into Decision” Microsoft SQL Server 2005 Business Intelligence.
Pentaho Open Source BI Goldwin. Pentaho Overview Pentaho is the commercial open source software for Business Pentaho is the commercial open source software.
Turning Numbers Into Knowledge Nate Moore MBA, CPA, FACMPE.
Business Intelligence components Introduction. Microsoft® SQL Server™ 2005 is a complete business intelligence (BI) platform that provides the features,
UNCLASSIFIED Business Intelligence and SharePoint 2010 Steve McDonnell.
Framework Designer Report Studio, Query Studio, Analysis Studio Cognos Connection TM1 (IM MOLAP), DB2 Cube Views (ROLAP) PowerPlay Z/Cognos.
Business User Experience Data Infrastructure and BI Platform Analysis Services Reporting Services Integration Services Master Data Services.
Microsoft Business Intelligence Gustavo Santade Business Intelligence Project Manager Improving Business Insight Building a cube using Analysis Services.
Understanding Analysis Services Architecture. Microsoft Data Warehousing Overview OLTP Source DTS DW Storage Analysis Services Clients OLE DB for OLAP,
1 © Goharian & Grossman 2003 Introduction to Data Mining (CS 422) Fall 2010.
SharePoint 2010 Business Intelligence Module 6: Analysis Services.
Business Intelligence in SQL Server 2005 Technical Overview Peter Blackburn Speaker, Trainer, Developer, Mentor, Author Windows Server Systems – SQL Server.
 First two parts of class ◦ Part 1: What is business intelligence and why should organizations consider incorporating more technology-related intelligence.
DATA WAREHOUSING IN SQL SERVER 2005/2008 BUSINESS INTELLIGENCE.
DAT336 SQL Server “Yukon” – The Future of Business Intelligence Jason Carlson Product Unit Manager SQL Server Microsoft Corporation Brian Welcker Microsoft.
TagHelper: Basics Part 1 Carolyn Penstein Rosé Carnegie Mellon University Funded through the Pittsburgh Science of Learning Center and The Office of Naval.
More value from data using Data Mining Allan Mitchell SQL Server MVP.
HDNUG 27-March-2007 SQL Server 2005 Suite as a Business Intelligence Solution.
Turning Numbers Into Knowledge Nate Moore MBA, CPA, FACMPE.
Introduction to SQL Server Data Mining Nick Ward SQL Server & BI Product Specialist Microsoft Australia Nick Ward SQL Server & BI Product Specialist Microsoft.
What makes a good interactive resume? Click for detailed information Multimedia Navigation Communication.
Datawarehouse A sneak preview. 2 Data Warehouse Approach An old idea with a new interest: Cheap Computing Power Special Purpose Hardware New Data Structures.
Reporting and Analysis With Microsoft Office. Reporting and Analysis Business User Reporting & Analysis OLAP Data Warehouse.
With Doug Atkins Getting Data Out of FASTER: Tips for the New & Experienced.
DAT377 Data Mining In SQL Server 2000 And SQL Server 2005 (Code Named “Yukon”) Paul Bradley Principal, Data Mining Technology Apollo Data Technologies.
Do It Strategically with Microsoft Business Intelligence! Bojan Ciric Strategic Consultant
CS 157B: Database Management Systems II April 10 Class Meeting Department of Computer Science San Jose State University Spring 2013 Instructor: Ron Mak.
Data Resource Management Agenda What types of data are stored by organizations? How are different types of data stored? What are the potential problems.
A summary only covers the main points A paraphrase has more details They both require you to put them in your own words Both have to be cited.
11 SAP & SQL Server 2005 Analysis Services Integration Microsoft Corporation SAP-Microsoft Competence Center (Tokyo) Microsoft Corporation SAP-Microsoft.
Fraud Detection Notes from the Field. Introduction Dejan Sarka –Data.
Copyright © 2016 Pearson Education, Inc. Modern Database Management 12 th Edition Jeff Hoffer, Ramesh Venkataraman, Heikki Topi CHAPTER 11: BIG DATA AND.
Data Mining With SQL Server Data Tools Mining Data Using Tools You Already Have.
Show Me Potential Customers Data Mining Approach Leila Etaati.
Data Resource Management – MGMT An overview of where we are right now SQL Developer OLAP CUBE 1 Sales Cube Data Warehouse Denormalized Historical.
نمايندگي استان يزد. نمايندگي استان يزد طراحی کسب و کار الکترونیکی ارائه کننده : محسن افسر قره باغ.
Detecting Web Attacks Using Multi-Stage Log Analysis
Serve as Director Funded by the Louisiana Department of Transportation and Development Developed LaCrash application to electronically capture crash.
Once Upon a Time: The Story of a Successful BI Implementation
Business Intelligence for a Tough Economy: Data Mining
MIS2502: Data Analytics Advanced Analytics - Introduction
Reporting and Analysis With Microsoft Office
Business Intelligence & Data Warehousing
Delivering Business Insight with SQL Server 2005
Unit B2 Day 5 This unit lasts for 3 weeks.
Data Mining It's not the size of your data it's what you do with it
Creating Novell Portal Services Gadgets: An Architectural Overview
3.1 Surface Area of Prisms October
K-Plex, Inc. We Develop Technology for… Personalization Integration
Data Mining in SQL Server 2005
Business Intelligence for Project Server/Online
MIS5101: Data Analytics Advanced Analytics - Introduction
UC San Diego Department of Mathematics
Microsoft SQL Server 2008 Reporting Services
TechEd /28/ :48 AM © 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered.
Introduction to NetDB2 IST210.
Delivering an End-to-End Business Intelligence Solution
From DTS to SSIS, Redesign or Upgrade
Analytics: Its More than Just Modeling
Day 5 Lesson Objectives I will be able to:
Equivalent Expressions
MIS2502: Data Analytics Introduction to Advanced Analytics
Base 10 and Powers of 10.
Data Warehousing Concepts
Advanced Dashboard Creation with PerformancePoint Services 2010
Unit 2: Research Lesson 04 and 05
MIS2502: Data Analytics Introduction to Advanced Analytics and R
Starter Activities GCSE Python.
6/17/ :03 AM © 2004 Microsoft Corporation. All rights reserved.
Presentation transcript:

Data Mining in SQL Server 2005 Corie Curcillo Central Ohio SQL SIG http://sqlsig.geodocs.com

Agenda Create Decision Tree and Naïve Bayes Data Mining Models View Mining Accuracy Charts http://msdn.microsoft.com/sql/learning/2005labs/default.aspx

What does Data Mining Do? Explores Your Data Finds Patterns Performs Predictions What Data Mining Does. I asked, I would avoid talking about what data mining is, rather tell the customer what is does. What it is is not very important really and generally confuses the customer – for example do you ask “What is a hammer?” Obviously not, because it doesn’t tell you much – is it interesting that the hammer is a piece of wood or fiberglass topped with a specifically shaped hunk of metal? No. What’s interesting about a hammer is that it drives nails. And that’s why we need to think about what data mining does. <advance> Data mining Explores your data Finds patterns And Performs predictions That’s it. People tend to view data mining as this mysterious dark art that few can master because it’s filled with advanced mathematical formulas, but really data mining is a tool that simply performs its function. How many people can make a hammer? How many people can use one?. Now many claims are made that data mining provides insight. I would say that’s a false statement. For example, I could use data mining to explore all the data from a hospital and if I found that the most important factor in determining whether a patient was delivering a baby was their gender, data mining didn’t provide insight – it did explore the data and find patterns. Obviously applying data mining takes some skill, but this is true of any tool. When I was building my son’s tree house, I sure was happy that my cousin the carpenter was around build the four sided roof.

BI Integration DTS OLAP Reporting Data Mining processing and results integrate directly into the operational pipeline OLAP Process Mining Models from Universal Dimensional Models (Cubes), use learned content to slice cubes based on data-specific patterns Reporting Embed Data Mining results directly into Reporting Services reports

Data Mining Data Flow .Net Historical Dataset Cube New Dataset Cube LOB Application Web .Net Native Model Browsing Mining Models Data Transform (DTS) Historical Dataset SQL OLE/DB Text File Reporting Prediction Cube Cube New Dataset Operations (DTS)